@article{
 title = {The use of pedigree, sib-pair and association studies of common diseases for genetic mapping and epidemiology},
 type = {article},
 year = {2004},
 identifiers = {[object Object]},
 keywords = {Chromosome Mapping,Epidemiologic Methods,Genetic Diseases, Inborn/epidemiology/*genetics,Humans,Linkage (Genetics),Pedigree,Phenotype,Research Support, U.S. Gov't, P.H.S.},
 pages = {1045-1051},
 volume = {36},
 id = {2711f28c-c5c7-3eef-be65-2590ead2eb8f},
 created = {2017-06-19T13:45:44.367Z},
 file_attached = {true},
 profile_id = {de68dde1-2ff3-3a4e-a214-ef424d0c7646},
 group_id = {b2078731-0913-33b9-8902-a53629a24e83},
 last_modified = {2017-06-19T13:45:44.502Z},
 tags = {04/12/23},
 read = {false},
 starred = {false},
 authored = {false},
 confirmed = {true},
 hidden = {false},
 source_type = {Journal Article},
 notes = {<m:note>Journal Article<m:linebreak/>Review</m:note>},
 abstract = {Efforts to identify gene variants associated with susceptibility to common diseases use three approaches: pedigree and affected sib-pair linkage studies and association studies of population samples. The different aims of these study designs reflect their derivation from biological versus epidemiological traditions. Similar principles regarding determination of the evidence levels required to consider the results statistically significant apply to both linkage and association studies, however. Such determination requires explicit attention to the prior probability of particular findings, as well as appropriate correction for multiple comparisons. For most common diseases, increasing the sample size in a study is a crucial step in achieving statistically significant genetic mapping results. Recent studies suggest that the technology and statistical methodology will soon be available to make well-powered studies feasible using any of these approaches.},
 bibtype = {article},
 author = {Freimer, N and Sabatti, C},
 journal = {Nat Genet},
 number = {10}
}

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